Camera location ordering has been addressed under the assumption that the orientation differences between cameras are small (e.g., <15 degrees) by estimating the intrinsic and extrinsic parameters of all cameras and the found 3D keypoints. This type of method is usually called “structure from motion” (SfM) which requires intensive computation of non-linear equations and optimizations. For larger orientation differences, the mainstream method is to track and identify the common moving objects over a period of time so the relative positions between each neighboring cameras are able to be inferred.
To deal with the problem of estimating multiple camera positions, the previous implementation is “Structure from Motion” (SfM) based on “Perspective n Point” (PnP) which requires at least three 3D points seen by three consecutive cameras; however, such points are harder to find if the difference of viewing angles between neighboring cameras is bigger than 15 degrees.